Search Results (261)

To elucidate the geochemical features of produced water in coalbed methane (CBM) wells of the Gujiao Block and their indicative significance for production, systematic testing of ion composition and total dissolved solids (TDS) of produced water from ten CBM wells was conducted through five discrete sampling campaigns over an 18-month period. Combined with production performance data, the spatiotemporal evolution patterns, controlling factors, and the response relationship with productivity were analyzed. The results show that the water chemistry type of produced water in the study area is mainly identified as the Na-HCO₃ type. The TDS averages 1716.62 mg/L. The hydrochemical characteristics are primarily controlled by water/rock interactions, with Na⁺ and K⁺ mainly derived from silicate mineral weathering and dissolution, coupled with cation exchange processes. The Na/Cl ratio suggests that halite dissolution contributes to both Na⁺ and Cl⁻, whereas the excess Na⁺ relative to Cl⁻ likely reflects cation exchange or dissolution of Na-bearing silicate minerals. As drainage proceeded, Na⁺ and K⁺ concentrations increased, Ca²⁺ decreased, Cl⁻ increased, and SO₄²⁻ first increased and then decreased. Spatially, TDS increases from north to south, with the central-southern region representing a stagnant groundwater zone. Productivity response analysis reveals that Na⁺, HCO₃⁻, and TDS all show a trend of initially slow increase followed by rapid increase with increasing gas production. A negative trend is observed between gas production and the concentrations of Cl⁻, Ca²⁺, Mg²⁺, and SO₄²⁻. The productivity response index for the Gujiao Block ranges from 3.75 to 42.43, with an average of 17.78. As the productivity response index increases, gas production initially decreases and then increases. The findings clarify the geochemical evolution mechanisms of produced water in the Gujiao Block, providing a scientific basis for productivity evaluation of CBM wells. Full article

The surface subsidence caused by coal mining is a geological environmental disaster that restricts the sustainable development of mining areas. Traditional monitoring methods have limitations in long-term and high-precision observation. Therefore, this paper proposes a synergistic monitoring framework for mining subsidence under thick loose layers by integrating Interferometric Synthetic Aperture Radar (InSAR) technology and Unmanned Aerial Vehicle (UAV) photogrammetry. The research results show: (1) UAV photogrammetry can accurately obtain the large gradient deformation at the center of the subsidence basin, while InSAR has better accuracy at the basin edge. The proposed fusion method is significantly superior to a single method. (2) The parameters obtained by the probability integral method based on the fused data are in good agreement with the parameters obtained by leveling measurement data, and the relative error of the parameters is less than 4%. (3) The thick and loose-layered mining areas have the characteristics of larger subsidence, steeper gradient at the center, slow convergence at the edge, and wide influence range. This study provides a new approach for precise subsidence monitoring, and the revealed subsidence characteristics provide a scientific basis for disaster assessment and mining optimization in similar areas. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) has become increasingly common, a trend driven by obesity, excess nutritional intake, and dysfunctional adipose tissue. While continuous dietary stress triggers adipose-tissue-derived lipotoxicity and disrupts hepatic metabolic homeostasis and provokes inflammation, the transcriptional scaffolds that mitigate this lipotoxicity remain incompletely understood. We investigated the role of zinc finger protein 90 (ZFP90) in defending against diet-induced metabolic stress and MASLD pathogenesis. Methods: Wild-type and ZFP90-knockout mice were subjected to a high-fat diet (HFD) to model nutrient-overload-induced MASLD. Hepatic phenotypes were characterized using metabolic profiling and RNA sequencing. Mechanistic dynamics were evaluated through protein interaction assays, and clinical relevance was validated using human MASLD liver biopsies. Results: ZFP90 deficiency significantly accelerated HFD-induced steatosis, systemic insulin resistance, and inflammatory infiltration. Crucially, ZFP90 depletion drove severe white adipose tissue (WAT) dysfunction, characterized by impaired lipogenic capacity, exacerbated lipolysis, and diminished local insulin signaling. This was accompanied by a pro-inflammatory secretory shift in WAT, evident from decreased Adipoq and increased Cd68/Ccl3 expression. In the liver, transcriptomic analysis revealed a profound induction of pathways related to fatty acid uptake and cytokine signaling. Mechanistically, ZFP90 forms a repressive complex with TRIM28, acting as a crucial molecular brake on NF-kB signaling. Loss of ZFP90 unleashes p65-mediated hyper-inflammation. Clinically, hepatic ZFP90 expression is significantly upregulated in patients with MASLD. Conclusions: ZFP90 is a novel regulator of immunometabolic homeostasis under dietary stress. By forming of complex with Trim28 to inhibit the nuclear translocation of NF-κB, ZFP90 suppresses pro-inflammatory responses and protects the liver from obesity-associated systemic lipotoxicity. These findings provide critical insights into the adipo-hepatic axis and highlight ZFP90 as a promising therapeutic target to mitigate the progression to metabolic dysfunction-associated steatohepatitis (MASH). Full article

The effectiveness of gas discharge depends on the geological conditions and drilling parameters. Investigating gas seepage behavior near boreholes under fluid–solid coupling conditions can provide theoretical support for scientifically determining the effective discharge radius (EDR) and ensuring mining safety. In this study, taking Xinyuan Coal Mine as the engineering background, a fluid–solid coupled model describing gas migration was developed. The effects of the discharge duration, borehole diameter, permeability, and borehole layout on the spatiotemporal evolution of gas around boreholes and EDR were investigated. The results indicate that gas pressure around the borehole continuously decreases with time, and the affected zone expands elliptically. The EDR exhibits a power-law relationship with time. Increasing the borehole diameter enlarges the EDR, with the effect being particularly significant in the initial stage of gas discharge. After 5 h of gas discharge, the EDR in high-permeability coal seams is approximately twice that in low-permeability coal seams. Compared to the triple-flower patterns, the square pattern produces a larger EDR at the same time. The EDR calculated based on the measured values of the drill cuttings volume S value and drill cuttings desorption gas volume K₁ value shows a high degree of consistency with the simulation results. After 5 h of gas discharge using the square pattern, the gas volume fraction at the upper corner of the working face dropped to the safe level of 6%, enabling mining to resume. Full article

The cumulative displacement of landslides in alpine regions is jointly affected by rainfall, temperature variation, freeze–thaw cycles, and other factors, and usually exhibits nonlinear, non-stationary, and multi-scale fluctuation characteristics. To improve the accuracy of landslide displacement prediction under complex environmental conditions, this study takes the Taker Tubek Village landslide in Gongliu County, Xinjiang, China, as the study object. Cumulative displacement data from GNSS02 and GNSS03, together with daily rainfall and daily mean temperature, were used to construct a SOO-VMD-CNN-TimeXer hybrid prediction model. First, SOO was employed to adaptively optimize the VMD parameters, and the cumulative displacement series were decomposed into multiple IMF components. Then, CNN was used to extract local fluctuation features, while TimeXer was applied to model long-term temporal dependencies and the effects of exogenous variables. Finally, the predicted results of all components were reconstructed to obtain the cumulative displacement prediction. The results show that the proposed model achieved high prediction accuracy at both GNSS02 and GNSS03. The MSE, MAE, MAPE, and R² values were 0.0158, 0.0960, 0.0112, and 0.9464 for GNSS02, and 0.0483, 0.1590, 0.0203, and 0.9946 for GNSS03, respectively, outperforming LSTM, Informer, iTransformer, Crossformer, and other models. The results indicate that the SOO-VMD-CNN-TimeXer model can effectively characterize the cumulative displacement evolution of landslides in alpine regions and provide technical support for landslide deformation trend forecasting and disaster early warning. Full article

Cucumber (Cucumis sativus L.) is an economically important vegetable crop worldwide, but its yield and quality improvement are often constrained by drought stress. To investigate the physiological and molecular mechanisms by which exogenous allantoin enhances drought tolerance in cucumber, cucumber seedlings were sprayed with 6 mM allantoin solution once (A1), three times (A3), or five times (A5), while control plants were sprayed with distilled water (CK1, CK3, CK5). Each treatment consisted of three biological replicates. After treatment, drought stress was simulated by irrigating with 20% polyethylene glycol 6000 (PEG-6000) solution. The results showed that the protective effect of exogenous allantoin against drought stress was cumulative. After five applications (A5), the net photosynthetic rate (Pn) and water-use efficiency (WUE) of the plants were significantly higher than those of the corresponding control (CK5) (p < 0.01). The detached leaf water loss rate progressively decreased with an increasing number of allantoin applications, while the total leaf wax content increased approximately 2-fold (p < 0.01). Measurements of wax content in different plant tissues indicated that allantoin mainly induced wax accumulation in aboveground organs (leaf, stem, and fruit epidermis), and this effect was validated in three commercial varieties. Integrated transcriptomic and metabolomic analyses revealed that the cucumber CsCER1 gene (encoding a very-long-chain aldehyde decarbonylase) is a core allantoin-responsive gene. After silencing CsCER1 using virus-induced gene silencing (VIGS), the allantoin-induced wax accumulation and drought tolerance were almost completely lost: the wilting severity and detached leaf water loss rate of the silenced plants were comparable to those of the empty vector control, and no significant increase in wax content was observed. This study reveals a novel mechanism by which exogenous allantoin enhances drought tolerance in cucumber through activating CsCER1-mediated cuticular wax synthesis, providing a theoretical basis for the chemical regulation of drought tolerance in cucurbit crops. Full article

As substation equipment continues to evolve toward higher voltage levels, larger capacities, and more complex operating conditions, voiceprint signals exhibit greater sensitivity and observability during the early stages of faults. However, traditional modeling approaches still suffer from limitations in capturing long-range temporal dependencies, suppressing noise interference, and adapting to unlabeled data. To address these issues, a state space model-based Mamba self-supervised voiceprint framework, termed MSANet, is proposed. A bidirectional state space scanning mechanism is introduced into the network architecture to avoid the high computational complexity of attention mechanisms while simultaneously preserving both global contextual correlations and local detail representations of voiceprint signals. In addition, a spectrum block masking-based self-supervised learning strategy is incorporated, enabling the model to extract stable time–frequency structural features even under unlabeled or limited labeled samples. Experimental results demonstrate that MSANet achieves high accuracy in voiceprint-related tasks. Furthermore, the lightweight version of the model maintains competitive performance while significantly reducing computational and storage overhead, indicating its feasibility for deployment on edge devices in resource-constrained scenarios such as substation environments. The proposed method provides a potential methodological basis for enhancing fault-related voiceprint feature extraction, representation learning, and future practical engineering deployment. Full article

In response to the need for a simple, non-destructive method for evaluating avocado ripeness, we measured chlorophyll-related fluorescence and chromaticity of the outer skin using simple optical equipment and evaluated their relationship with whole-fruit compression (wfc), which was used as a firmness-based ripeness index. A compact system consisting of a blue LED excitation source and a small spectrometer was used to measure fluorescence spectra, and a commercially available colorimeter was used to evaluate chromaticity. Hass avocado samples purchased from multiple retail stores in Japan and stored for different periods were examined. The combination of the fluorescence intensity ratio I₇₄₀/I₆₈₅ and the lightness parameter L* showed a moderate correlation with wfc, with R² = 0.48. The fluorescence ratio I₇₄₀/I₆₈₅ was treated not as a direct measure of chlorophyll content, but as a spectral index associated with ripening-related changes in avocado skin, including chlorophyll-related fluorescence and skin optical properties. These results suggest that the combination of simple blue LED-excited fluorescence and chromaticity measurements may be useful as a practical screening approach for roughly estimating avocado ripeness in commercially available fruit. Full article

Two reconstruction methods for constraint and load parameters of aero-engine pipelines based on intelligent optimization algorithms are proposed in this paper. First, a simplified finite element model (FEM) of the aero-engine pipeline structure is established, and its reliability is validated by comparing simulation data with experimental data. Second, a reconstruction algorithm for spring constraint parameters and pipeline load parameters based on the improved particle swarm optimization (IPSO) algorithm is developed on the MATLAB data analysis and ANSYS simulation platforms, which completes the reconstruction calculation of parameters such as spring constraint stiffness and applied harmonic excitation. For harmonic excitation parameter reconstruction, the maximum error of this algorithm reaches 24.9%, revealing its significant inapplicability to load parameter reconstruction. To solve this problem, a load reconstruction method based on the conjugate gradient method (CGM) is further proposed to achieve accurate reconstruction of pipeline load parameters, which mitigates the large reconstruction error of the IPSO algorithm under working conditions with multiple loads. Under 5% noise interference, the maximum error of the CGM is merely 5.16%. Finally, experimental verification of harmonic excitation amplitude reconstruction is performed using the CGM with lower reconstruction errors. Experimental results indicate that the maximum error is 14.24% for harmonic excitation amplitude reconstruction, which verifies the high applicability of the conjugate gradient algorithm to load reconstruction of aero-engine pipelines. Full article

Genomic sequencing can reveal potentially life-threatening clinically actionable secondary findings in healthy individuals. Little is known about the spectrum and frequency of secondary findings in healthy people in Russia. Here, we analyzed whole-genome sequences of 42,826 healthy volunteers from urban populations across Russia, focusing on known pathogenic and likely pathogenic variants of 81 genes associated with treatable or preventable monogenic diseases listed in the American College of Medical Genetics and Genomics’ Secondary Findings recommendations (ACMG SF v3.2). Based on the ClinVar 20250421 version, secondary findings were detected in 1186 (2.76%) participants. Cancer phenotypes were the most common category of secondary findings present in 565 (1.32%) participants, followed by cardiovascular phenotypes (454 individuals, 1.05%). Genes harboring the most frequent variants were BRCA1 (151 variants), BRCA2 (100), RYR1 (93), and LDLR (71). In addition, we found 238 potential loss-of-function variants in dominant ACMG SF v3.2 list genes in 280 (0.65%) participants, which, if confirmed by orthogonal methods, could increase the frequency of secondary findings to 3.41%. A study of such depth and scale was performed for the first time in the Russian population. Full article

This paper considers a numerically stable discrete-time representation of the three-dimensional Constant Turn (CT) motion model within the Interacting Multiple Model (IMM) framework for radar tracking of maneuvering aerial targets. Classical discrete CT models used in Kalman-filter-based tracking contain singular expressions in the vicinity of zero and near-zero turn rates, which may degrade estimation accuracy and impair numerical robustness. To address this problem, a Maclaurin-series-based discretization of the three-dimensional CT model is developed, in which the state transition matrix and the process-noise-related matrices are approximated in polynomial form. Linear, quadratic, and cubic approximations are constructed and analyzed. The proposed CT model is integrated into a three-model IMM algorithm together with the Constant Velocity (CV) and Constant Acceleration (CA) models. The study includes both an internal comparison of Maclaurin approximations of different orders and an external comparison with the classical CT discretization and a Padé-based reference discretization. Numerical experiments are performed for representative three-dimensional maneuvering scenarios under radar measurement conditions. The obtained results show that the proposed discretization eliminates singular behavior near zero turn rate while preserving the tracking capability of the IMM estimator. The comparative analysis demonstrates that the quadratic Maclaurin approximation provides the most favorable trade-off between modeling accuracy, numerical stability, and computational cost. It yields tracking performance close to higher-order approximations and competitive with the Padé-based reference approach, while remaining simpler for practical implementation in real-time radar tracking systems. These results indicate that the proposed quadratic approximation is a suitable solution for maneuvering aerial target tracking in three-dimensional radar applications. Full article

Currently, there is no existing methodology within commercially available software packages for accurately simulating the gradual evaporation of the aqueous phase in batch thermomechanical dehydration processes involving highly stable water-hydrocarbon emulsions. This limitation constitutes a significant obstacle to the widespread industrial implementation of a promising approach for liquid hydrocarbon waste disposal, which relies on the evaporation of the aqueous phase under intensive stirring conditions, ultimately producing a hydrocarbon product with residual water content. In this study, the widely used Aspen HYSYS V12 software was employed to model these processes. The primary objective was to identify the most appropriate thermodynamic model accurately describing vapor–liquid phase transitions during the boiling of the aqueous phase in highly stable water–hydrocarbon emulsions, with water content ranging from 2 to 60% by weight. The modeling of the gradual boiling process was divided into several sequential stages, each representing a single evaporation step. The initial feedstock temperature was set at 90 °C, with subsequent stages involving temperature increments of 5 °C until the residual water content in the product fell below 0.5% by weight. Four thermodynamic models were evaluated for their ability to predict phase equilibria: Peng–Robinson, Wilson, UNIQUAC, and NRTL. It was observed that the Peng–Robinson model poorly describes the dehydration process, as it predicts water evaporation only at 100 °C, which contradicts experimental evidence indicating that evaporation occurs over a broader temperature range. The Wilson model significantly overestimates boiling points, reaching values up to 290 °C. Although the UNIQUAC model accurately reflects the process at higher water contents, it results in elevated energy consumption, necessitating substantial superheating of the feedstock up to 220 °C. The NRTL model provided the best correlation (among studied thermodynamic models) with experimental data, providing an average relative deviation of 3.68% and effectively capturing the two-stage evaporation mechanism: initial removal of free water at 100–110 °C, followed by bound moisture evaporation at temperatures approaching 160 °C. Vaporization rates were also examined across all models. The Peng–Robinson approach predicted the highest vaporization peaks but was the least representative of actual process conditions. Notably, in the NRTL model, the peak vaporization rates were 1.9 to 2.7 times higher than those estimated using the UNIQUAC and Wilson models. This parameter is critical for the optimal selection and design of subsequent condensation equipment. Based on these findings, the NRTL thermodynamic model is recommended for the industrial-scale implementation of thermomechanical dehydration processes involving heavy hydrocarbon feedstocks, given its accuracy in modeling phase transitions and the temperature-dependent vapor generation rates derived from sequential equilibrium flash calculations. Full article

Objectives: Diagnostic delay in pulmonary tuberculosis remains a significant barrier to effective disease control, even in low-incidence settings. This study aimed to identify factors associated with total delay and its components among adults with pulmonary tuberculosis in such a setting. Patients and methods: A retrospective observational study was conducted on adults with pulmonary tuberculosis treated at a tuberculosis care centre in Croatia. Total delay was defined as the interval between symptom onset and treatment initiation. Data were collected through structured patient interviews using a standardized questionnaire, medical record review, and routine tuberculosis notification forms from the national public health registry. Sociodemographic and clinical predictors were evaluated using multivariable linear and logistic regression analyses. Results: Among 116 participants, the median total delay was 85 days (interquartile range 48.5–155.3). Rural residence was the strongest independent predictor, with patients experiencing an 88% longer delay than urban residents (p = 0.006). Individuals living in one-person households had a 49% longer delay (p = 0.047). Absence of chest pain was associated with shorter delay (−38%, p = 0.032) and lower odds of extreme delay (odds ratio 0.39, p = 0.047). Retired status independently predicted prolonged health system delay (42.1 days longer) and treatment delay (3.4 days longer). Conclusion: Prolonged delay may become increasingly important in the context of population ageing and changing household structures. Targeted strategies focused on rural, retired, and people living in one-person households may improve the timeliness of tuberculosis detection in settings where declining incidence can reduce clinical suspicion. Full article

Geopolymer concretes are increasingly regarded as advanced construction materials for applications requiring high thermal and chemical resistance. This article is a continuation of previously published research and focuses on the mechanical behaviour of geopolymer concretes containing aggregates made of foamed geopolymers and lightweight mineral aggregates, such as expanded clay and perlite, intended for use in chimney flue components. The aim of the study was to determine the influence of lightweight aggregates on the relationship between thermal insulation and the strength parameters of geopolymer concretes intended for use at elevated temperatures. Foamed geopolymer aggregates were produced by a controlled chemical foaming process, followed by grinding to specific grain sizes, yielding highly porous aggregates with low thermal conductivity, reaching approximately 0.075–0.099 W/(m·K). These aggregates were used as lightweight fillers in geopolymer concretes based on class F fly ash activated with alkaline solutions. The resulting composites were designed to combine low density and high thermal insulation with adequate mechanical strength. The mechanical properties of the developed concretes were assessed on the basis of compressive strength tests on cubic specimens and tensile strength in beam bending tests, carried out in accordance with standards. The results presented confirm that the use of foamed geopolymer aggregates enables a simultaneous increase in thermal insulation and the design of ultra-lightweight structural elements with sufficient load-bearing capacity for chimney systems (including suspended ones). This combination of low thermal conductivity, reduced mass, and appropriate mechanical properties makes geopolymer concretes with lightweight mineral and geopolymer aggregates a promising alternative to traditional ceramic materials. Full article

The utilization of immunomodulatory nanomaterials, i.e., leveraging their unique properties to enhance immune responses, represents a transformative approach for the treatment of various diseases. Recent advancements in nanotechnology have enabled the design of nanomaterials capable of delivering immunomodulatory agents in a targeted manner, such as cytokines, antibodies, and nucleic acids, to specific cells or tissues involved in immune regulation. These nanomaterials, including nanoparticles, liposomes, nanogels, nanoemulsions, dendrimers, MXenes and extracellular vesicles, have been increasingly tailored to modulate immune responses with precision and efficacy. This targeted approach not only enhances therapeutic outcomes but also reduces off-target effects, minimizing systemic toxicity. In this review, an overview of immunomodulatory nanomaterials and their biomedical applications are highlighted. Herein, we have discussed different types of nanomaterials and their design strategies, interactions with different immune system components (macrophages, dendritic cells (DCs), neutrophils, T lymphocytes (CD4⁺ helper T-cells, CD8⁺ cytotoxic T-cells, regulatory T-cells/Tregs, and memory T-cells), and B lymphocytes), and immunomodulation mechanisms. Furthermore, nanomaterial-based immunomodulation strategies to enhance cancer immunotherapy, wound healing, and bone regeneration and the treatment of infectious diseases, autoimmune diseases, and allergy and are discussed in detail. In addition to therapeutic applications, selected nanomaterial platforms demonstrate significant potential in pharmaceutical formulations by improving drug stability, controlled release, and bioavailability, as well as in cosmetology through skin-targeted delivery, anti-inflammatory activity, immune protection, and enhanced tissue regeneration. Finally, clinical trial updates, challenges and future prospects are outlined. Key findings indicate that lipid-based, polymeric, inorganic nanoparticles and dendrimers provide complementary advantages for immunomodulation, including efficient delivery, controlled release, multifunctionality, and precise immune targeting. Despite safety, regulatory, and scalability challenges, these systems show strong potential for advancing precision and personalized medicine. Taken together, these innovations hold great promise for personalized medicine approaches, wherein nanomaterials can be tailored to individual patient profiles for more effective and precise disease treatment and prevention strategies. This review focuses primarily on the mechanistic interactions between immunomodulatory nanomaterials and immune cells, including macrophages, dendritic cells, neutrophils, T lymphocytes, and B lymphocytes, rather than providing an exhaustive treatment of physicochemical optimization parameters such as particle size or surface modification chemistry, which fall outside the defined scope of this work. Full article